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TypeError: fwd(): incompatible function arguments. The following argument types are supported,求助是否我flash-attn安装不对 #70

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MRziyang opened this issue Mar 5, 2025 · 1 comment

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@MRziyang
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MRziyang commented Mar 5, 2025

我的pip环境

再执行这一段代码的时候,出现以下报错

from evo2 import Evo2
evo2_model = Evo2(model_name='evo2_7b',local_path='/evo_prj/evo2_7b.pt')
import torch

sequence = 'ACGT'
input_ids = torch.tensor(
    evo2_model.tokenizer.tokenize(sequence),
    dtype=torch.int,
).unsqueeze(0).to('cuda:0')
outputs, _ = evo2_model(input_ids)

我的报错内容
`File "/evo2/vortex/vortex/ops/attn_interface.py", line 466, in forward
out_padded, softmax_lse, S_dmask, rng_state = _wrapped_flash_attn_forward(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/miniconda3/envs/evo2/lib/python3.11/site-packages/torch/_ops.py", line 1116, in call
return self._op(*args, **(kwargs or {}))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/miniconda3/envs/evo2/lib/python3.11/site-packages/torch/_library/autograd.py", line 113, in autograd_impl
result = forward_no_grad(*args, Metadata(keyset, keyword_only_args))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/miniconda3/envs/evo2/lib/python3.11/site-packages/torch/_library/autograd.py", line 40, in forward_no_grad
result = op.redispatch(keyset & _C._after_autograd_keyset, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/miniconda3/envs/evo2/lib/python3.11/site-packages/torch/_ops.py", line 721, in redispatch
return self._handle.redispatch_boxed(keyset, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/miniconda3/envs/evo2/lib/python3.11/site-packages/torch/_library/custom_ops.py", line 324, in backend_impl
result = self._backend_fns[device_type](*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/miniconda3/envs/evo2/lib/python3.11/site-packages/torch/_compile.py", line 32, in inner
return disable_fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/miniconda3/envs/evo2/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 632, in _fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/opt/miniconda3/envs/evo2/lib/python3.11/site-packages/torch/_library/custom_ops.py", line 367, in wrapped_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/evo2/vortex/vortex/ops/attn_interface.py", line 61, in _flash_attn_forward
out, softmax_lse, S_dmask, rng_state = flash_attn_gpu.fwd(
^^^^^^^^^^^^^^^^^^^
TypeError: fwd(): incompatible function arguments. The following argument types are supported:
1. (arg0: torch.Tensor, arg1: torch.Tensor, arg2: torch.Tensor, arg3: Optional[torch.Tensor], arg4: Optional[torch.Tensor], arg5: float, arg6: float, arg7: bool, arg8: int, arg9: int, arg10: bool, arg11: Optional[torch.Generator]) -> list[torch.Tensor]

Invoked with: tensor([[[[-2.6245e-02, -4.2419e-03, -3.0212e-03, ..., -2.4219e-01,
-2.1484e-01, -1.9922e-01],
[-1.5198e-02, 1.3885e-03, 3.9062e-02, ..., 3.9551e-02,
-3.3447e-02, 3.8818e-02],
[ 5.0659e-03, 2.0996e-02, -9.7046e-03, ..., 8.3008e-02,
1.4355e-01, 1.1523e-01],
...,
[-3.8818e-02, -1.2878e-02, 1.4465e-02, ..., 1.6406e-01,
-1.4771e-02, 1.3281e-01],
[ 4.5898e-02, 4.7607e-03, -7.2327e-03, ..., 2.2339e-02,
3.2812e-01, 1.2891e-01],
[-1.3245e-02, 1.4526e-02, 3.1738e-02, ..., -7.7637e-02,
-2.5781e-01, -3.5400e-02]],

     [[-1.5869e-02, -6.4850e-04,  5.3711e-03,  ..., -2.7930e-01,
       -2.7148e-01, -2.4805e-01],
      [-2.8198e-02, -1.7578e-02,  2.5635e-02,  ...,  1.8433e-02,
       -6.4392e-03,  3.8330e-02],
      [ 7.0190e-03,  2.4170e-02, -2.4719e-03,  ...,  1.0107e-01,
        1.4941e-01,  1.3574e-01],
      ...,
      [-3.7354e-02, -5.1880e-03,  1.0742e-02,  ...,  1.9629e-01,
       -2.5635e-03,  1.7773e-01],
      [ 3.8818e-02,  1.2695e-02, -2.0905e-03,  ...,  4.8218e-03,
        3.7305e-01,  1.3379e-01],
      [-1.5503e-02,  1.3794e-02,  5.0781e-02,  ..., -1.0059e-01,
       -3.0273e-01, -1.7944e-02]],

     [[-1.5747e-02, -3.9482e-04,  5.7068e-03,  ..., -2.7930e-01,
       -2.7148e-01, -2.4902e-01],
      [-2.8198e-02, -1.7944e-02,  2.5269e-02,  ...,  1.9897e-02,
       -6.3171e-03,  3.7842e-02],
      [ 7.0496e-03,  2.4170e-02, -2.5635e-03,  ...,  1.0156e-01,
        1.4941e-01,  1.3574e-01],
      ...,
      [-3.6865e-02, -4.4556e-03,  1.0986e-02,  ...,  1.9727e-01,
       -2.3499e-03,  1.7773e-01],
      [ 3.9307e-02,  1.2878e-02, -2.5024e-03,  ...,  4.0894e-03,
        3.7305e-01,  1.3379e-01],
      [-1.4954e-02,  1.3367e-02,  5.0537e-02,  ..., -1.0059e-01,
       -3.0469e-01, -1.7212e-02]],

     [[-1.5320e-02, -1.8692e-04,  5.7373e-03,  ..., -2.7930e-01,
       -2.7148e-01, -2.4902e-01],
      [-2.9053e-02, -1.7700e-02,  2.6978e-02,  ...,  2.0508e-02,
       -4.0588e-03,  3.7598e-02],
      [ 6.9885e-03,  2.4536e-02, -2.6703e-03,  ...,  1.0059e-01,
        1.4746e-01,  1.3477e-01],
      ...,
      [-3.6621e-02, -6.0120e-03,  1.1169e-02,  ...,  1.9531e-01,
       -2.8839e-03,  1.7773e-01],
      [ 3.9307e-02,  1.3123e-02, -1.5945e-03,  ...,  4.9744e-03,
        3.7305e-01,  1.3379e-01],
      [-1.5076e-02,  1.3245e-02,  5.1270e-02,  ..., -1.0059e-01,
       -3.0469e-01, -1.9897e-02]]]], device='cuda:0', dtype=torch.bfloat16), tensor([[[[-0.0064, -0.0396, -0.0522,  ...,  0.0767,  0.0776,  0.0859],
      [-0.0231,  0.0332,  0.0366,  ..., -0.0977,  0.0708,  0.0344],
      [ 0.0129,  0.0004, -0.0181,  ..., -0.1885, -0.1309, -0.1885],
      ...,
      [ 0.0505,  0.0039, -0.0084,  ..., -0.0562,  0.0197, -0.1060],
      [-0.0376, -0.0364, -0.0025,  ...,  0.0064, -0.0908, -0.2578],
      [ 0.0317, -0.0096,  0.0270,  ...,  0.1787,  0.0737, -0.0747]],

     [[-0.0118, -0.0229, -0.0027,  ...,  0.1206,  0.1123,  0.1221],
      [-0.0177, -0.0102,  0.0035,  ..., -0.0566, -0.0053, -0.0129],
      [ 0.0295,  0.0027, -0.0105,  ..., -0.2656, -0.1963, -0.2676],
      ...,
      [ 0.0315, -0.0116, -0.0342,  ..., -0.1133,  0.0096, -0.1279],
      [-0.0063, -0.0361, -0.0110,  ...,  0.0315, -0.1494, -0.3125],
      [ 0.0442, -0.0098, -0.0011,  ...,  0.2637,  0.1328, -0.0352]],

     [[-0.0123, -0.0226, -0.0025,  ...,  0.1211,  0.1133,  0.1230],
      [-0.0172, -0.0110,  0.0030,  ..., -0.0566, -0.0055, -0.0128],
      [ 0.0300,  0.0023, -0.0111,  ..., -0.2656, -0.1963, -0.2676],
      ...,
      [ 0.0311, -0.0115, -0.0344,  ..., -0.1138,  0.0094, -0.1279],
      [-0.0067, -0.0369, -0.0113,  ...,  0.0322, -0.1494, -0.3125],
      [ 0.0442, -0.0095, -0.0005,  ...,  0.2656,  0.1328, -0.0366]],

     [[-0.0129, -0.0227, -0.0030,  ...,  0.1206,  0.1143,  0.1226],
      [-0.0172, -0.0110,  0.0048,  ..., -0.0559, -0.0056, -0.0117],
      [ 0.0298,  0.0024, -0.0109,  ..., -0.2656, -0.1973, -0.2676],
      ...,
      [ 0.0304, -0.0126, -0.0356,  ..., -0.1152,  0.0088, -0.1289],
      [-0.0066, -0.0364, -0.0116,  ...,  0.0311, -0.1504, -0.3125],
      [ 0.0454, -0.0106, -0.0013,  ...,  0.2637,  0.1328, -0.0374]]]],
   device='cuda:0', dtype=torch.bfloat16), tensor([[[[ 1.3855e-02,  1.0986e-02,  9.8877e-03,  ...,  3.1982e-02,
       -2.5482e-03,  1.0315e-02],
      [ 2.1118e-02,  1.9287e-02, -2.2827e-02,  ..., -1.9653e-02,
        1.4282e-02,  4.1809e-03],
      [ 1.1719e-02, -1.1169e-02, -1.7090e-02,  ...,  8.4839e-03,
       -1.1475e-02, -6.9885e-03],
      ...,
      [-1.1292e-03,  7.5989e-03, -5.5237e-03,  ..., -3.8300e-03,
        4.0283e-03, -5.8289e-03],
      [-2.3438e-02,  2.6978e-02,  8.5831e-04,  ..., -1.6235e-02,
       -4.0283e-03,  7.9346e-03],
      [-5.2795e-03, -8.7891e-03,  1.7700e-02,  ...,  1.5076e-02,
       -4.0894e-03,  2.3071e-02]],

     [[-1.7090e-03, -1.3962e-03,  7.5340e-05,  ..., -4.7913e-03,
        1.8692e-03, -2.2221e-04],
      [-1.8845e-03, -2.6245e-03,  2.0294e-03,  ...,  1.9836e-03,
       -9.9945e-04, -5.5313e-04],
      [ 3.7670e-05,  7.4387e-04,  2.3193e-03,  ..., -7.7057e-04,
        6.4850e-04,  4.6921e-04],
      ...,
      [-1.7738e-04, -1.2665e-03, -1.3351e-04,  ...,  1.6499e-04,
       -2.3556e-04,  2.2697e-04],
      [ 2.3804e-03, -3.7689e-03, -6.4850e-04,  ...,  9.3079e-04,
        3.0708e-04, -4.0817e-04],
      [-1.7738e-04,  7.0572e-04,  1.5717e-03,  ..., -2.5177e-03,
        2.6512e-04, -2.4872e-03]],

     [[-1.8158e-03, -1.3809e-03,  4.3154e-05,  ..., -4.3945e-03,
        1.9226e-03, -3.2425e-04],
      [-2.1057e-03, -2.3804e-03,  2.2888e-03,  ...,  1.8997e-03,
       -1.1520e-03, -4.9591e-04],
      [-1.0300e-04,  1.2665e-03,  2.5482e-03,  ..., -5.1880e-04,
        7.7820e-04,  6.7139e-04],
      ...,
      [-2.6512e-04, -1.3046e-03,  1.6117e-04,  ...,  1.9169e-04,
       -2.3174e-04,  2.5368e-04],
      [ 2.3956e-03, -3.6774e-03, -8.1253e-04,  ...,  1.0910e-03,
        6.6376e-04, -3.9673e-04],
      [-4.0531e-05,  9.6893e-04,  1.7471e-03,  ..., -2.4567e-03,
        3.8910e-04, -2.7161e-03]],

     [[-1.9836e-03, -1.4725e-03, -9.2506e-05,  ..., -4.4556e-03,
        1.7548e-03, -4.2343e-04],
      [-2.0752e-03, -2.7008e-03,  2.1820e-03,  ...,  2.2583e-03,
       -1.2360e-03, -3.7003e-04],
      [-1.7357e-04,  8.2397e-04,  2.0752e-03,  ..., -8.0872e-04,
        8.8882e-04,  2.8038e-04],
      ...,
      [-2.0409e-04, -1.3351e-03,  2.4986e-04,  ...,  1.8692e-04,
       -2.4796e-04,  2.4605e-04],
      [ 2.5024e-03, -3.7689e-03, -5.3787e-04,  ...,  8.6594e-04,
        5.3024e-04, -5.3406e-04],
      [ 5.0354e-04,  9.9182e-04,  2.1362e-03,  ..., -2.6245e-03,
        5.9128e-04, -2.8992e-03]]]], device='cuda:0', dtype=torch.bfloat16), None, None, 0.0, 0.08838834764831845, True, -1, -1, 0.0, False, None`

我的pip环境是
joblib 1.3.2
jsonlines 4.0.0
kiwisolver 1.4.5
lazy_import_plus 0.0.2
lightning-utilities 0.10.0
lm-dataformat 0.0.20
lm-eval 0.3.0
local_flash_attn 0.0.0 /evo2/vortex/vortex/ops/attn
lxml 4.9.4
Mako 1.3.5
Markdown 3.5.1
markdown-it-py 3.0.0
MarkupSafe 2.1.3
matplotlib 3.8.2
matplotlib-inline 0.1.6
mbstrdecoder 1.1.3
mdurl 0.1.2
mkl_fft 1.3.10
mkl_random 1.2.7
mkl-service 2.4.0
ml_collections 0.1.1
modelcif 0.9
mpi4py 3.1.4
mpmath 1.3.0
msgpack 1.0.7
multidict 6.0.4
multiprocess 0.70.15
mypy-extensions 1.0.0
networkx 3.2.1
ninja 1.11.1.1
nltk 3.8.1
nodeenv 1.8.0
numexpr 2.8.8
numpy 1.26.2
nvidia-cublas-cu12 12.4.5.8
nvidia-cuda-cupti-cu12 12.4.127
nvidia-cuda-nvrtc-cu12 12.4.127
nvidia-cuda-runtime-cu12 12.4.127
nvidia-cudnn-cu12 9.1.0.70
nvidia-cufft-cu12 11.2.1.3
nvidia-curand-cu12 10.3.5.147
nvidia-cusolver-cu12 11.6.1.9
nvidia-cusparse-cu12 12.3.1.170
nvidia-ml-py 12.560.30
nvidia-nccl-cu12 2.21.5
nvidia-nvjitlink-cu12 12.4.127
nvidia-nvtx-cu12 12.4.127
oauthlib 3.2.2
omegaconf 2.3.0
openai 1.6.1
opentelemetry-api 1.27.0
opentelemetry-sdk 1.27.0
opentelemetry-semantic-conventions 0.48b0
opt-einsum 3.3.0
packaging 23.2
pandas 2.1.4
parso 0.8.3
pathvalidate 3.2.0
peft 0.7.1
pexpect 4.9.0
Pillow 10.1.0
pip 24.2
platformdirs 4.2.2
pluggy 1.3.0
polars 1.2.1
portalocker 2.8.2
pre_commit 4.0.1
prompt-toolkit 3.0.43
protobuf 3.20.3
psutil 6.0.0
ptyprocess 0.7.0
pure-eval 0.2.2
py 1.11.0
py-cpuinfo 9.0.0
py-spy 0.3.14
pyarrow 14.0.2
pyarrow-hotfix 0.6
pyasn1 0.5.1
pyasn1-modules 0.3.0
pybind11 2.11.1
pycodestyle 2.11.1
pycountry 23.12.11
pydantic 2.9.0
pydantic_core 2.23.2
Pygments 2.17.2
pynvml 11.5.0
pyparsing 3.1.1
pyproject_hooks 1.2.0
PySocks 1.7.1
pytablewriter 1.2.0
pytest 7.4.3
pytest-cov 4.1.0
pytest-forked 1.6.0
pytest-xdist 3.5.0
python-dateutil 2.8.2
pytorch-lightning 2.1.3
pytz 2023.3.post1
PyYAML 6.0.2
regex 2023.10.3
requests 2.32.3
requests-oauthlib 1.3.1
responses 0.18.0
rich 13.9.2
rouge_score 0.1.2
rsa 4.9
ruff 0.1.1
s3transfer 0.10.2
sacrebleu 1.5.0
safetensors 0.4.1
scikit-learn 1.3.2
scipy 1.11.4
seaborn 0.13.1
sentencepiece 0.1.99
sentry-sdk 2.13.0
setproctitle 1.3.3
setuptools 74.1.0
shtab 1.7.0
six 1.16.0
smmap 5.0.1
sniffio 1.3.0
SQLAlchemy 2.0.34
sqlitedict 2.1.0
sqlparse 0.5.1
stack-data 0.6.3
stua 0.3
sympy 1.13.1
tabledata 1.3.3
tabulate 0.9.0
tcolorpy 0.1.4
tenacity 9.0.0
tensorboard 2.5.0
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
threadpoolctl 3.2.0
tokenizers 0.15.0
torch 2.5.1
torchaudio 2.4.1
torchmetrics 1.4.0.post0
torchvision 0.15.2a0
tqdm 4.66.1
tqdm-multiprocess 0.0.11
traitlets 5.14.0
transformer_engine 1.10.0+08a85d3
transformers 4.36.2
triton 3.1.0
trl 0.7.11
typeguard 2.13.3
typepy 1.3.2
types-python-dateutil 2.9.0.20241003
typing_extensions 4.9.0
typing-inspect 0.9.0
tyro 0.7.3
tzdata 2023.3
ujson 5.9.0
urllib3 2.2.2
virtualenv 20.26.6
vortex 0.0.2 /evo2/vortex
wandb 0.17.7
wandb-workspaces 0.1.8
wcwidth 0.2.12
Werkzeug 3.0.1
wheel 0.41.2
wrapt 1.16.0
xxhash 3.4.1
yarl 1.9.4
zipp 3.20.0
zstandard 0.22.0

@MRziyang MRziyang changed the title TypeError: fwd(): incompatible function arguments. The following argument types are supported TypeError: fwd(): incompatible function arguments. The following argument types are supported,求助是否我flash-attn安装姿势不对 Mar 5, 2025
@MRziyang MRziyang changed the title TypeError: fwd(): incompatible function arguments. The following argument types are supported,求助是否我flash-attn安装姿势不对 TypeError: fwd(): incompatible function arguments. The following argument types are supported,求助是否我flash-attn安装不对 Mar 5, 2025
@kawabata-tomoko
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Same problem. I solved by uninstalling flash-attn and reinstalling evo2(may not need install flash-attn by manual)

pip uninstall -y flash-attn transformer-engine
pip install transformer_engine[pytorch]==1.13
pip install . -vv

and here's my pip environment :

(savanna) root@g0024:~/zhengyulong/zhengyulong/evo2# pip list
Package                  Version        Editable project location
------------------------ -------------- ---------------------------------------------
annotated-types          0.7.0
antlr4-python3-runtime   4.9.3
arrow                    1.3.0
asttokens                3.0.0
autopep8                 2.3.2
biopython                1.85
boto3                    1.37.15
botocore                 1.37.15
build                    1.2.2.post1
cattrs                   24.1.2
causal-conv1d            1.5.0.post8
certifi                  2025.1.31
cfgv                     3.4.0
charset-normalizer       3.4.1
clang-format             20.1.0
click                    8.1.8
cmake                    3.31.6
comm                     0.2.2
coverage                 7.7.0
debugpy                  1.8.11
decorator                5.1.1
deepspeed                0.16.4
dill                     0.3.8
distlib                  0.3.9
docker-pycreds           0.4.0
einops                   0.8.0
et_xmlfile               2.0.0
evo2                     0.1.0
execnet                  2.1.1
executing                2.1.0
filelock                 3.18.0
fsspec                   2025.3.0
gitdb                    4.0.12
GitPython                3.1.44
hjson                    3.1.0
huggingface-hub          0.29.3
identify                 2.6.9
idna                     3.10
importlib_metadata       8.6.1
iniconfig                2.0.0
ipykernel                6.29.5
ipython                  8.30.0
ipywidgets               8.1.5
jedi                     0.19.2
Jinja2                   3.1.6
jmespath                 1.0.1
jupyter_client           8.6.3
jupyter_core             5.7.2
jupyterlab_widgets       3.0.13
lazy_import_plus         0.0.2
local_flash_attn         0.0.0          /root/zhengyulong/evo2/vortex/vortex/ops/attn
loguru                   0.7.3
markdown-it-py           3.0.0
MarkupSafe               3.0.2
matplotlib-inline        0.1.7
mdurl                    0.1.2
mpmath                   1.3.0
msgpack                  1.1.0
multiprocess             0.70.16
networkx                 3.4.2
ninja                    1.11.1.3
nodeenv                  1.9.1
numpy                    2.2.4
nvidia-cublas-cu12       12.4.5.8
nvidia-cuda-cupti-cu12   12.4.127
nvidia-cuda-nvrtc-cu12   12.4.127
nvidia-cuda-runtime-cu12 12.4.127
nvidia-cudnn-cu12        9.1.0.70
nvidia-cufft-cu12        11.2.1.3
nvidia-curand-cu12       10.3.5.147
nvidia-cusolver-cu12     11.6.1.9
nvidia-cusparse-cu12     12.3.1.170
nvidia-cusparselt-cu12   0.6.2
nvidia-ml-py             12.570.86
nvidia-nccl-cu12         2.21.5
nvidia-nvjitlink-cu12    12.4.127
nvidia-nvtx-cu12         12.4.127
omegaconf                2.3.0
openpyxl                 3.1.5
opt_einsum               3.4.0
packaging                24.2
parso                    0.8.4
pexpect                  4.9.0
pillow                   11.1.0
pip                      25.0
platformdirs             4.3.6
pluggy                   1.5.0
pre_commit               4.0.1
prompt_toolkit           3.0.48
protobuf                 5.29.3
psutil                   7.0.0
ptyprocess               0.7.0
pure_eval                0.2.3
py                       1.11.0
py-cpuinfo               9.0.0
pybind11                 2.13.6
pycodestyle              2.12.1
pydantic                 2.10.6
pydantic_core            2.27.2
Pygments                 2.18.0
pyproject_hooks          1.2.0
pytest                   8.3.5
pytest-cov               6.0.0
pytest-forked            1.6.0
pytest-xdist             3.6.1
python-dateutil          2.9.0.post0
PyYAML                   6.0.2
RapidFuzz                3.10.1
regex                    2024.11.6
requests                 2.32.3
requests-cache           1.2.1
retrying                 1.3.4
rich                     13.9.2
ring-flash-attn          0.1.4
ruff                     0.1.1
s3transfer               0.11.4
scipy                    1.15.2
sentencepiece            0.2.0
sentry-sdk               2.23.1
setproctitle             1.3.5
setuptools               75.8.0
six                      1.17.0
smmap                    5.0.2
stack-data               0.6.3
sympy                    1.13.1
thefuzz                  0.22.1
tokenizers               0.20.1
torch                    2.5.1
torchaudio               2.6.0
torchvision              0.21.0
tornado                  6.4.2
tqdm                     4.67.1
traitlets                5.14.3
transformer_engine       1.13.0
transformer_engine_cu12  1.13.0
transformer_engine_torch 1.13.0
triton                   3.1.0
types-python-dateutil    2.9.0.20241206
typing_extensions        4.12.2
url-normalize            1.4.3
urllib3                  2.3.0
virtualenv               20.29.3
vortex                   0.0.2          /root/zhengyulong/evo2/vortex
wandb                    0.19.8
wcwidth                  0.2.13
wheel                    0.45.1
widgetsnbextension       4.0.13
xxhash                   3.5.0
zipp                     3.21.0

or you can just try the methods which described in issues/27

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